In a retrospective study, Perera et al. used a dense neural network (DNN) machine learning model incorporating age, PSA, free PSA, and free-to-total PSA ratio to improve the diagnosis of PCa, and showed an AUC of 0.72 for DNN compared to 0.65 (free-to-total PSA ratio) and 0.63 (PSA only) [14]. The gene discussed is KLK3; the disease is posterior cortical atrophy.